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Navigation and Localization for Autonomous Marine Vehicle
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Navigation and Localization for Autonomous Marine Vehicle

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (5 July 2023) | Viewed by 3422

Special Issue Editors

Dr. Bruno Miguel Ferreira

E-Mail Website
Guest Editor
Technology and Science, Institute for Systems and Computer Engineering, 4200-465 Porto, Portugal
Interests: marine robotics; autonomous underwater vehicle (AUV); autonomous surface vehicles (ASV); guidance; control; coordination; localization; estimation; sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Nuno A. Cruz

E-Mail Website1 Website2
Guest Editor
Technology and Science, Institute for Systems and Computer Engineering, 4200-465 Porto, Portugal
Interests: marine robotics; adaptive sampling; control; guidance; autonomous underwater vehicles (AUV); autonomous surface vehicles (ASV); underwater system design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The harshness of the sea and the characteristics of the environment pose considerable challenges to the navigation of marine vehicles. The research on autonomous marine vehicles has attempted to overcome these barriers for decades, dedicating valuable efforts to mechatronics, instrumentation, control, estimation, perception, and ultimately to localization and navigation. This Special Issue aims to gather the latest developments in these domains, from cutting-edge approaches to experimental validation of new methods. The topics of interest are the following:

  • New sensing approaches;
  • Localization and Tracking;
  • Guidance and Control;
  • Perception and Mapping;

Papers with a strong theoretical background, rigorous experimental evaluation of approaches, and comprehensive surveys are encouraged.

Dr. Bruno Miguel Ferreira
Dr. Nuno A. Cruz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • navigation
  • localization
  • guidance
  • AUV/UUV
  • ASV/USV
  • surface/underwater perception and mapping

Published Papers (2 papers)

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Research

16 pages, 860 KiB  
Article
Path Planning Method for Underwater Gravity-Aided Inertial Navigation Based on PCRB
by Bo Wang and Tijing Cai
J. Mar. Sci. Eng. 2023, 11(5), 993; https://doi.org/10.3390/jmse11050993 - 07 May 2023
Cited by 2 | Viewed by 1534
Abstract
Gravity-aided inertial navigation system (GAINS) is an important development in autonomous underwater vehicle (AUV) navigation. An effective path planning algorithm plays an important role in the performance of navigation in long-term underwater missions. By combining the gravity information obtained at each position with [...] Read more.
Gravity-aided inertial navigation system (GAINS) is an important development in autonomous underwater vehicle (AUV) navigation. An effective path planning algorithm plays an important role in the performance of navigation in long-term underwater missions. By combining the gravity information obtained at each position with the error information from the INS, the posterior Cramér-Rao bound (PCRB) of GAINS is derived in this paper. The PCRB is the estimated lower bound of position variance for navigation along the planned trajectory. And the sum of PCRB is used as the minimum cost from the initial state to the current state in the state space, and the position error prediction variance of inertial navigation system (INS) is used as the minimum estimated cost of the path from the current state to the goal state in the A* algorithm. Thus, a path planning method with optimal navigation accuracy is proposed. According to simulation results, traveling along the path planned by the proposed method can rapidly improve the positioning accuracy while consuming just slightly more distance. Even when measuring noise changes, the planned path can still maintain optimal positioning accuracy, and high positioning accuracy is possible for any trajectory located within a certain range of the planned path. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicle)
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21 pages, 2802 KiB  
Article
Comparative Analysis of 3D LiDAR Scan-Matching Methods for State Estimation of Autonomous Surface Vessel
by Haichao Wang, Yong Yin and Qianfeng Jing
J. Mar. Sci. Eng. 2023, 11(4), 840; https://doi.org/10.3390/jmse11040840 - 15 Apr 2023
Cited by 7 | Viewed by 1536
Abstract
Accurate positioning and state estimation of surface vessels are prerequisites to achieving autonomous navigation. Recently, the rapid development of 3D LiDARs has promoted the autonomy of both land and aerial vehicles, which has aroused the interest of researchers in the maritime community accordingly. [...] Read more.
Accurate positioning and state estimation of surface vessels are prerequisites to achieving autonomous navigation. Recently, the rapid development of 3D LiDARs has promoted the autonomy of both land and aerial vehicles, which has aroused the interest of researchers in the maritime community accordingly. In this paper, the state estimation schemes based on 3D LiDAR scan matching are explored in depth. Firstly, the iterative closest point (ICP) and normal distribution transformation (NDT) algorithms and their variants are introduced in detail. Besides, ten representative registration algorithms are selected from the variants for comparative analysis. Two types of experiments are designed by utilizing the field test data of an ASV equipped with a 3D LiDAR. Both the accuracy and real-time performance of the selected algorithms are systemically analyzed based on the experimental results. It follows that ICP and Levenberg–Marquardt iterative closest point (LMICP) methods perform well on single-frame experiments, while the voxelized generalized iterative closest point (FastVGICP) and multi-threaded optimization generalized iterative closest point (FastGICP) methods have the best performance on continuous-frame experiments. However, all methods have lower accuracy during fast turning. Consequently, the limitations of current methods are discussed in detail, which provides insights for future exploration of accurate state estimation based on 3D LiDAR for ASVs. Full article
(This article belongs to the Special Issue Navigation and Localization for Autonomous Marine Vehicle)
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